{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "a7609b21", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T05:22:58.209175Z", "iopub.status.busy": "2025-03-25T05:22:58.208968Z", "iopub.status.idle": "2025-03-25T05:22:58.409110Z", "shell.execute_reply": "2025-03-25T05:22:58.408707Z" } }, "outputs": [], "source": [ "import sys\n", "import os\n", "sys.path.append(os.path.abspath(os.path.join(os.getcwd(), '../..')))\n", "\n", "# Path Configuration\n", "from tools.preprocess import *\n", "\n", "# Processing context\n", "trait = \"Glioblastoma\"\n", "cohort = \"GSE39144\"\n", "\n", "# Input paths\n", "in_trait_dir = \"../../input/GEO/Glioblastoma\"\n", "in_cohort_dir = \"../../input/GEO/Glioblastoma/GSE39144\"\n", "\n", "# Output paths\n", "out_data_file = \"../../output/preprocess/Glioblastoma/GSE39144.csv\"\n", "out_gene_data_file = \"../../output/preprocess/Glioblastoma/gene_data/GSE39144.csv\"\n", "out_clinical_data_file = \"../../output/preprocess/Glioblastoma/clinical_data/GSE39144.csv\"\n", "json_path = \"../../output/preprocess/Glioblastoma/cohort_info.json\"\n" ] }, { "cell_type": "markdown", "id": "00b29fe7", "metadata": {}, "source": [ "### Step 1: Initial Data Loading" ] }, { "cell_type": "code", "execution_count": 2, "id": "9a1b3d7e", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T05:22:58.410892Z", "iopub.status.busy": "2025-03-25T05:22:58.410711Z", "iopub.status.idle": "2025-03-25T05:22:58.665744Z", "shell.execute_reply": "2025-03-25T05:22:58.665374Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Background Information:\n", "!Series_title\t\"Expression data of human induced pluripotent stem cells (hiPSCs), human embryonic stem cells (hESCs) and those differentiated cells.\"\n", "!Series_summary\t\"We examined hiPSCs, hESCs and those differentiated cells to identify pluripotent signature genes, differentiation marker genes and relationship between expression and phenotypes.\"\n", "!Series_summary\t\"Additionally, we performed microarray experiments to examine gene expression in human tissues. This data was used for comparison with hESCs, hiPSCs and those differentiated cells.\"\n", "!Series_summary\t\"A total of 22 tissues (bone marrow, cerebellum, colon, cortex, fetal brain, heart, kidney, liver, lung, pancreas, prostate, salivary gland, skeletal muscle, small intestine, spinal cord, spleen, stomach, testes, thymus, thyroid, trachea and uterus) were examined.\"\n", "!Series_overall_design\t\"The hiPSCs, hESCs and those differentiated cells were cultured, and their cDNAs were used for microarray analysis.\"\n", "!Series_overall_design\t\"Total RNA isolated from cultivated cells and human tissues were labeled and hybridized to the GeneChip Human Genome U133 Plus 2.0 Array according to the manufacturer's protocol.\"\n", "Sample Characteristics Dictionary:\n", "{0: ['cell line: KhES1', 'cell line: KhES2', 'cell line: KhES3', 'cell line: 201B6', 'cell line: 201B7', 'cell line: 253G1', 'cell line: 253G4', 'cell line: 409B2', 'cell line: 414C2', 'cell type: human dermal fibroblast', 'cell type: neural stem/progenitor cells oh-NSC-3-fb', 'cell type: neural stem/progenitor cells oh-NSC-7-fb', 'cell type: glioma-initiating cells GDC21', 'cell type: glioma-initiating cells GDC36', 'cell type: glioma-initiating cells GDC40', 'ethnicity: Caucasian'], 1: ['source: derived from inner cell mass of Japanese blastocysts', 'source: induced from human dermal fibroblast of 36-year-old Caucasian female', 'source: differentiated from KhES1 ES', 'source: differentiated from KhES2 ES', 'source: differentiated from KhES3 ES', 'source: differentiated from 201B6 iPS', 'source: differentiated from 201B7 iPS', 'source: differentiated from 253G1 iPS', 'source: differentiated from 253G4 iPS', 'source: differentiated from 409B2 iPS', 'source: differentiated from 414C2 iPS', 'source: 36-year-old Caucasian female', 'source: Cultured neural stem/progenitor cells from forebrain tissues from Japanese human fetuses aged 10 gestational week', 'source: Cultured neural stem/progenitor cells from forebrain tissues from Japanese human fetuses aged 9 gestational week', 'source: Cultured glioma-initiating cells from glioblastoma tissues from patient', 'gender: male and female', 'gender: male', 'gender: female'], 2: ['gender: female', 'gender: male', 'gender: pooled', 'gender: pooled male', 'gender: pooled female'], 3: ['culture days: P27', 'culture days: P26', 'culture days: P18', 'culture days: P15', 'culture days: P22', 'culture days: P29', 'culture days: 30 days from differentiation', 'culture days: 42 days from differentiation', 'culture days: 66 days from differentiation', 'culture days: 40 days from differentiation', 'culture days: 76 days from differentiation', 'culture days: P11', 'culture days: 203 days', 'culture days: 215 days', 'culture days: 227 days', 'culture days: 292 days', 'culture days: 304 days', 'culture days: 316 days', 'culture days: P9', 'culture days: P5', 'culture days: P6', 'culture days: -']}\n" ] } ], "source": [ "from tools.preprocess import *\n", "# 1. Identify the paths to the SOFT file and the matrix file\n", "soft_file, matrix_file = geo_get_relevant_filepaths(in_cohort_dir)\n", "\n", "# 2. Read the matrix file to obtain background information and sample characteristics data\n", "background_prefixes = ['!Series_title', '!Series_summary', '!Series_overall_design']\n", "clinical_prefixes = ['!Sample_geo_accession', '!Sample_characteristics_ch1']\n", "background_info, clinical_data = get_background_and_clinical_data(matrix_file, background_prefixes, clinical_prefixes)\n", "\n", "# 3. Obtain the sample characteristics dictionary from the clinical dataframe\n", "sample_characteristics_dict = get_unique_values_by_row(clinical_data)\n", "\n", "# 4. Explicitly print out all the background information and the sample characteristics dictionary\n", "print(\"Background Information:\")\n", "print(background_info)\n", "print(\"Sample Characteristics Dictionary:\")\n", "print(sample_characteristics_dict)\n" ] }, { "cell_type": "markdown", "id": "f69dcc04", "metadata": {}, "source": [ "### Step 2: Dataset Analysis and Clinical Feature Extraction" ] }, { "cell_type": "code", "execution_count": null, "id": "0bc5a354", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "c0a0c4ee", "metadata": {}, "source": [ "### Step 3: Dataset Analysis and Clinical Feature Extraction" ] }, { "cell_type": "code", "execution_count": 3, "id": "9f344576", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T05:22:58.667175Z", "iopub.status.busy": "2025-03-25T05:22:58.667060Z", "iopub.status.idle": "2025-03-25T05:22:58.675622Z", "shell.execute_reply": "2025-03-25T05:22:58.675295Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Clinical data file not found at ../../input/GEO/Glioblastoma/GSE39144/clinical.pickle\n" ] } ], "source": [ "# Clinical data availability check\n", "clinical_file = os.path.join(in_cohort_dir, \"clinical.pickle\")\n", "\n", "if os.path.exists(clinical_file):\n", " with open(clinical_file, 'rb') as f:\n", " clinical_data = pickle.load(f)\n", " \n", " # Print the keys and first few values for each key in the sample characteristics\n", " sample_characteristics = clinical_data.get('sample_characteristics', {})\n", " \n", " # Print the background information and sample characteristics to analyze\n", " print(\"Background Information:\")\n", " for key, value in clinical_data.get('background_info', {}).items():\n", " print(f\"{key}: {value}\")\n", " \n", " print(\"\\nSample Characteristics:\")\n", " for key, values in sample_characteristics.items():\n", " unique_values = list(set(values))\n", " print(f\"Row {key}: {unique_values[:5]}{'...' if len(unique_values) > 5 else ''}\")\n", " \n", " # Check gene expression availability\n", " background_info = clinical_data.get('background_info', {})\n", " platform = background_info.get('platform', '')\n", " summary = background_info.get('summary', '')\n", " \n", " # Check if this is gene expression data (not miRNA or methylation)\n", " is_gene_available = True\n", " if 'mirna' in platform.lower() or 'methylation' in summary.lower() or 'mirna' in summary.lower():\n", " is_gene_available = False\n", " \n", " # Identify rows for trait, age, and gender\n", " trait_row = None\n", " age_row = None\n", " gender_row = None\n", " \n", " # Define conversion functions\n", " def convert_trait(value):\n", " if value is None:\n", " return None\n", " \n", " # Extract value after colon if present\n", " if ':' in value:\n", " value = value.split(':', 1)[1].strip()\n", " \n", " # Convert to binary based on common glioblastoma indicators\n", " value = value.lower()\n", " if 'glioblastoma' in value or 'gbm' in value or 'grade iv' in value or 'grade 4' in value:\n", " return 1\n", " elif 'normal' in value or 'control' in value or 'non-tumor' in value:\n", " return 0\n", " else:\n", " return None\n", " \n", " def convert_age(value):\n", " if value is None:\n", " return None\n", " \n", " # Extract value after colon if present\n", " if ':' in value:\n", " value = value.split(':', 1)[1].strip()\n", " \n", " # Try to extract numeric age value\n", " numeric_part = re.search(r'(\\d+)', value)\n", " if numeric_part:\n", " return float(numeric_part.group(1))\n", " else:\n", " return None\n", " \n", " def convert_gender(value):\n", " if value is None:\n", " return None\n", " \n", " # Extract value after colon if present\n", " if ':' in value:\n", " value = value.split(':', 1)[1].strip()\n", " \n", " # Convert to binary (female=0, male=1)\n", " value = value.lower()\n", " if 'female' in value or 'f' == value.strip():\n", " return 0\n", " elif 'male' in value or 'm' == value.strip():\n", " return 1\n", " else:\n", " return None\n", " \n", " # Search for trait, age, and gender in sample characteristics\n", " for key, values in sample_characteristics.items():\n", " unique_values = list(set(values))\n", " \n", " # Skip if only one unique value (constant feature)\n", " if len(unique_values) <= 1:\n", " continue\n", " \n", " # Check for trait information\n", " sample_value = values[0].lower() if values else \"\"\n", " if ('glioblastoma' in sample_value or 'gbm' in sample_value or 'tumor' in sample_value or \n", " 'cancer' in sample_value or 'grade' in sample_value or 'diagnosis' in sample_value):\n", " trait_row = key\n", " \n", " # Check for age information\n", " if ('age' in sample_value or 'year' in sample_value) and not trait_row == key:\n", " age_row = key\n", " \n", " # Check for gender information\n", " if ('gender' in sample_value or 'sex' in sample_value or 'male' in sample_value or \n", " 'female' in sample_value) and not trait_row == key and not age_row == key:\n", " gender_row = key\n", " \n", " # Check for trait availability\n", " is_trait_available = trait_row is not None\n", " \n", " # Conduct initial filtering on usability\n", " validate_and_save_cohort_info(\n", " is_final=False,\n", " cohort=cohort,\n", " info_path=json_path,\n", " is_gene_available=is_gene_available,\n", " is_trait_available=is_trait_available\n", " )\n", " \n", " # Extract clinical features if trait data is available\n", " if is_trait_available:\n", " # Convert DataFrame to standard format\n", " clinical_df = pd.DataFrame(sample_characteristics)\n", " \n", " # Extract selected clinical features\n", " selected_clinical_df = geo_select_clinical_features(\n", " clinical_df=clinical_df,\n", " trait=trait,\n", " trait_row=trait_row,\n", " convert_trait=convert_trait,\n", " age_row=age_row,\n", " convert_age=convert_age if age_row is not None else None,\n", " gender_row=gender_row,\n", " convert_gender=convert_gender if gender_row is not None else None\n", " )\n", " \n", " # Preview the extracted clinical data\n", " print(\"\\nPreview of extracted clinical data:\")\n", " preview = preview_df(selected_clinical_df)\n", " for key, values in preview.items():\n", " print(f\"{key}: {values}\")\n", " \n", " # Save clinical data to CSV\n", " os.makedirs(os.path.dirname(out_clinical_data_file), exist_ok=True)\n", " selected_clinical_df.to_csv(out_clinical_data_file, index=False)\n", " print(f\"Clinical data saved to {out_clinical_data_file}\")\n", " else:\n", " print(\"No trait data available, skipping clinical feature extraction.\")\n", "else:\n", " print(f\"Clinical data file not found at {clinical_file}\")\n", " is_gene_available = False\n", " is_trait_available = False\n", " \n", " # Save metadata for unavailable data\n", " validate_and_save_cohort_info(\n", " is_final=False,\n", " cohort=cohort,\n", " info_path=json_path,\n", " is_gene_available=is_gene_available,\n", " is_trait_available=is_trait_available\n", " )\n" ] }, { "cell_type": "markdown", "id": "e7ccfe04", "metadata": {}, "source": [ "### Step 4: Gene Data Extraction" ] }, { "cell_type": "code", "execution_count": 4, "id": "4eacce3d", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T05:22:58.676791Z", "iopub.status.busy": "2025-03-25T05:22:58.676678Z", "iopub.status.idle": "2025-03-25T05:22:58.922581Z", "shell.execute_reply": "2025-03-25T05:22:58.922126Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Found data marker at line 92\n", "Header line: \"ID_REF\"\t\"GSM956840\"\t\"GSM956841\"\t\"GSM956842\"\t\"GSM956843\"\t\"GSM956844\"\t\"GSM956845\"\t\"GSM956846\"\t\"GSM956847\"\t\"GSM956848\"\t\"GSM956849\"\t\"GSM956850\"\t\"GSM956851\"\t\"GSM956852\"\t\"GSM956853\"\t\"GSM956854\"\t\"GSM956855\"\t\"GSM956856\"\t\"GSM956857\"\t\"GSM956858\"\t\"GSM956859\"\t\"GSM956860\"\t\"GSM956861\"\t\"GSM956862\"\t\"GSM956863\"\t\"GSM956864\"\t\"GSM956865\"\t\"GSM956866\"\t\"GSM956867\"\t\"GSM956868\"\t\"GSM956869\"\t\"GSM956870\"\t\"GSM956871\"\t\"GSM956872\"\t\"GSM956873\"\t\"GSM956874\"\t\"GSM956875\"\t\"GSM956876\"\t\"GSM956877\"\t\"GSM956878\"\t\"GSM956879\"\t\"GSM956880\"\t\"GSM956881\"\t\"GSM956882\"\t\"GSM956883\"\t\"GSM956884\"\t\"GSM956885\"\t\"GSM956886\"\t\"GSM956887\"\t\"GSM956888\"\t\"GSM956889\"\t\"GSM956890\"\t\"GSM956891\"\t\"GSM956892\"\t\"GSM956893\"\t\"GSM956894\"\t\"GSM956895\"\t\"GSM956896\"\t\"GSM956897\"\t\"GSM956898\"\t\"GSM956899\"\t\"GSM956900\"\t\"GSM956901\"\t\"GSM956902\"\t\"GSM956903\"\t\"GSM956904\"\t\"GSM956905\"\t\"GSM956906\"\t\"GSM956907\"\t\"GSM956908\"\t\"GSM956909\"\t\"GSM956910\"\t\"GSM956911\"\t\"GSM956912\"\t\"GSM956913\"\t\"GSM956914\"\t\"GSM956915\"\t\"GSM956916\"\n", "First data line: \"1007_s_at\"\t10.84\t11.76\t11.30\t10.83\t11.39\t11.25\t11.09\t11.40\t11.19\t11.73\t10.93\t11.75\t11.16\t12.27\t11.66\t12.10\t11.73\t12.01\t12.21\t11.83\t12.07\t11.78\t12.46\t11.80\t12.04\t11.81\t11.66\t12.55\t12.29\t12.29\t12.31\t12.41\t12.02\t12.41\t12.33\t12.40\t12.64\t11.98\t11.54\t11.44\t12.18\t12.00\t12.09\t12.30\t12.46\t10.35\t13.57\t13.31\t13.29\t13.23\t13.26\t13.19\t13.07\t12.73\t13.39\t8.91\t11.71\t11.79\t12.09\t12.75\t10.12\t12.21\t10.09\t10.98\t12.30\t11.69\t12.70\t10.85\t11.28\t13.14\t9.59\t11.15\t10.16\t11.28\t12.11\t12.51\t11.49\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Index(['1007_s_at', '1053_at', '117_at', '121_at', '1255_g_at', '1294_at',\n", " '1316_at', '1320_at', '1405_i_at', '1431_at', '1438_at', '1487_at',\n", " '1494_f_at', '1552256_a_at', '1552257_a_at', '1552258_at', '1552261_at',\n", " '1552263_at', '1552264_a_at', '1552266_at'],\n", " dtype='object', name='ID')\n" ] } ], "source": [ "# 1. Get the file paths for the SOFT file and matrix file\n", "soft_file, matrix_file = geo_get_relevant_filepaths(in_cohort_dir)\n", "\n", "# 2. First, let's examine the structure of the matrix file to understand its format\n", "import gzip\n", "\n", "# Peek at the first few lines of the file to understand its structure\n", "with gzip.open(matrix_file, 'rt') as file:\n", " # Read first 100 lines to find the header structure\n", " for i, line in enumerate(file):\n", " if '!series_matrix_table_begin' in line:\n", " print(f\"Found data marker at line {i}\")\n", " # Read the next line which should be the header\n", " header_line = next(file)\n", " print(f\"Header line: {header_line.strip()}\")\n", " # And the first data line\n", " first_data_line = next(file)\n", " print(f\"First data line: {first_data_line.strip()}\")\n", " break\n", " if i > 100: # Limit search to first 100 lines\n", " print(\"Matrix table marker not found in first 100 lines\")\n", " break\n", "\n", "# 3. Now try to get the genetic data with better error handling\n", "try:\n", " gene_data = get_genetic_data(matrix_file)\n", " print(gene_data.index[:20])\n", "except KeyError as e:\n", " print(f\"KeyError: {e}\")\n", " \n", " # Alternative approach: manually extract the data\n", " print(\"\\nTrying alternative approach to read the gene data:\")\n", " with gzip.open(matrix_file, 'rt') as file:\n", " # Find the start of the data\n", " for line in file:\n", " if '!series_matrix_table_begin' in line:\n", " break\n", " \n", " # Read the headers and data\n", " import pandas as pd\n", " df = pd.read_csv(file, sep='\\t', index_col=0)\n", " print(f\"Column names: {df.columns[:5]}\")\n", " print(f\"First 20 row IDs: {df.index[:20]}\")\n", " gene_data = df\n" ] }, { "cell_type": "markdown", "id": "4b3428ba", "metadata": {}, "source": [ "### Step 5: Gene Identifier Review" ] }, { "cell_type": "code", "execution_count": 5, "id": "5b013c53", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T05:22:58.924007Z", "iopub.status.busy": "2025-03-25T05:22:58.923878Z", "iopub.status.idle": "2025-03-25T05:22:58.926101Z", "shell.execute_reply": "2025-03-25T05:22:58.925649Z" } }, "outputs": [], "source": [ "# The identifiers in this dataset appear to be Affymetrix probe IDs (e.g., \"1007_s_at\", \"1053_at\") \n", "# rather than standard human gene symbols like BRCA1, TP53, etc.\n", "# These probe IDs need to be mapped to their corresponding gene symbols for biological interpretation.\n", "\n", "requires_gene_mapping = True\n" ] }, { "cell_type": "markdown", "id": "704f7393", "metadata": {}, "source": [ "### Step 6: Gene Annotation" ] }, { "cell_type": "code", "execution_count": 6, "id": "b3d8d604", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T05:22:58.927480Z", "iopub.status.busy": "2025-03-25T05:22:58.927373Z", "iopub.status.idle": "2025-03-25T05:22:59.856354Z", "shell.execute_reply": "2025-03-25T05:22:59.855783Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Examining SOFT file structure:\n", "Line 0: ^DATABASE = GeoMiame\n", "Line 1: !Database_name = Gene Expression Omnibus (GEO)\n", "Line 2: !Database_institute = NCBI NLM NIH\n", "Line 3: !Database_web_link = http://www.ncbi.nlm.nih.gov/geo\n", "Line 4: !Database_email = geo@ncbi.nlm.nih.gov\n", "Line 5: ^SERIES = GSE39144\n", "Line 6: !Series_title = Expression data of human induced pluripotent stem cells (hiPSCs), human embryonic stem cells (hESCs) and those differentiated cells.\n", "Line 7: !Series_geo_accession = GSE39144\n", "Line 8: !Series_status = Public on May 09 2023\n", "Line 9: !Series_submission_date = Jul 05 2012\n", "Line 10: !Series_last_update_date = May 10 2023\n", "Line 11: !Series_summary = We examined hiPSCs, hESCs and those differentiated cells to identify pluripotent signature genes, differentiation marker genes and relationship between expression and phenotypes.\n", "Line 12: !Series_summary = Additionally, we performed microarray experiments to examine gene expression in human tissues. This data was used for comparison with hESCs, hiPSCs and those differentiated cells.\n", "Line 13: !Series_summary = A total of 22 tissues (bone marrow, cerebellum, colon, cortex, fetal brain, heart, kidney, liver, lung, pancreas, prostate, salivary gland, skeletal muscle, small intestine, spinal cord, spleen, stomach, testes, thymus, thyroid, trachea and uterus) were examined.\n", "Line 14: !Series_overall_design = The hiPSCs, hESCs and those differentiated cells were cultured, and their cDNAs were used for microarray analysis.\n", "Line 15: !Series_overall_design = Total RNA isolated from cultivated cells and human tissues were labeled and hybridized to the GeneChip Human Genome U133 Plus 2.0 Array according to the manufacturer's protocol.\n", "Line 16: !Series_type = Expression profiling by array\n", "Line 17: !Series_type = Third-party reanalysis\n", "Line 18: !Series_contributor = Yohei,,Okada\n", "Line 19: !Series_contributor = Fuyuki,,Miya\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "Gene annotation preview:\n", "{'ID': ['1007_s_at', '1053_at', '117_at', '121_at', '1255_g_at'], 'GB_ACC': ['U48705', 'M87338', 'X51757', 'X69699', 'L36861'], 'SPOT_ID': [nan, nan, nan, nan, nan], 'Species Scientific Name': ['Homo sapiens', 'Homo sapiens', 'Homo sapiens', 'Homo sapiens', 'Homo sapiens'], 'Annotation Date': ['Oct 6, 2014', 'Oct 6, 2014', 'Oct 6, 2014', 'Oct 6, 2014', 'Oct 6, 2014'], 'Sequence Type': ['Exemplar sequence', 'Exemplar sequence', 'Exemplar sequence', 'Exemplar sequence', 'Exemplar sequence'], 'Sequence Source': ['Affymetrix Proprietary Database', 'GenBank', 'Affymetrix Proprietary Database', 'GenBank', 'Affymetrix Proprietary Database'], 'Target Description': ['U48705 /FEATURE=mRNA /DEFINITION=HSU48705 Human receptor tyrosine kinase DDR gene, complete cds', 'M87338 /FEATURE= /DEFINITION=HUMA1SBU Human replication factor C, 40-kDa subunit (A1) mRNA, complete cds', \"X51757 /FEATURE=cds /DEFINITION=HSP70B Human heat-shock protein HSP70B' gene\", 'X69699 /FEATURE= /DEFINITION=HSPAX8A H.sapiens Pax8 mRNA', 'L36861 /FEATURE=expanded_cds /DEFINITION=HUMGCAPB Homo sapiens guanylate cyclase activating protein (GCAP) gene exons 1-4, complete cds'], 'Representative Public ID': ['U48705', 'M87338', 'X51757', 'X69699', 'L36861'], 'Gene Title': ['discoidin domain receptor tyrosine kinase 1 /// microRNA 4640', 'replication factor C (activator 1) 2, 40kDa', \"heat shock 70kDa protein 6 (HSP70B')\", 'paired box 8', 'guanylate cyclase activator 1A (retina)'], 'Gene Symbol': ['DDR1 /// MIR4640', 'RFC2', 'HSPA6', 'PAX8', 'GUCA1A'], 'ENTREZ_GENE_ID': ['780 /// 100616237', '5982', '3310', '7849', '2978'], 'RefSeq Transcript ID': ['NM_001202521 /// NM_001202522 /// NM_001202523 /// NM_001954 /// NM_013993 /// NM_013994 /// NR_039783 /// XM_005249385 /// XM_005249386 /// XM_005249387 /// XM_005249389 /// XM_005272873 /// XM_005272874 /// XM_005272875 /// XM_005272877 /// XM_005275027 /// XM_005275028 /// XM_005275030 /// XM_005275031 /// XM_005275162 /// XM_005275163 /// XM_005275164 /// XM_005275166 /// XM_005275457 /// XM_005275458 /// XM_005275459 /// XM_005275461 /// XM_006715185 /// XM_006715186 /// XM_006715187 /// XM_006715188 /// XM_006715189 /// XM_006715190 /// XM_006725501 /// XM_006725502 /// XM_006725503 /// XM_006725504 /// XM_006725505 /// XM_006725506 /// XM_006725714 /// XM_006725715 /// XM_006725716 /// XM_006725717 /// XM_006725718 /// XM_006725719 /// XM_006725720 /// XM_006725721 /// XM_006725722 /// XM_006725827 /// XM_006725828 /// XM_006725829 /// XM_006725830 /// XM_006725831 /// XM_006725832 /// XM_006726017 /// XM_006726018 /// XM_006726019 /// XM_006726020 /// XM_006726021 /// XM_006726022 /// XR_427836 /// XR_430858 /// XR_430938 /// XR_430974 /// XR_431015', 'NM_001278791 /// NM_001278792 /// NM_001278793 /// NM_002914 /// NM_181471 /// XM_006716080', 'NM_002155', 'NM_003466 /// NM_013951 /// NM_013952 /// NM_013953 /// NM_013992', 'NM_000409 /// XM_006715073'], 'Gene Ontology Biological Process': ['0001558 // regulation of cell growth // inferred from electronic annotation /// 0001952 // regulation of cell-matrix adhesion // inferred from electronic annotation /// 0006468 // protein phosphorylation // inferred from electronic annotation /// 0007155 // cell adhesion // traceable author statement /// 0007169 // transmembrane receptor protein tyrosine kinase signaling pathway // inferred from electronic annotation /// 0007565 // female pregnancy // inferred from electronic annotation /// 0007566 // embryo implantation // inferred from electronic annotation /// 0007595 // lactation // inferred from electronic annotation /// 0008285 // negative regulation of cell proliferation // inferred from electronic annotation /// 0010715 // regulation of extracellular matrix disassembly // inferred from mutant phenotype /// 0014909 // smooth muscle cell migration // inferred from mutant phenotype /// 0016310 // phosphorylation // inferred from electronic annotation /// 0018108 // peptidyl-tyrosine phosphorylation // inferred from electronic annotation /// 0030198 // extracellular matrix organization // traceable author statement /// 0038063 // collagen-activated tyrosine kinase receptor signaling pathway // inferred from direct assay /// 0038063 // collagen-activated tyrosine kinase receptor signaling pathway // inferred from mutant phenotype /// 0038083 // peptidyl-tyrosine autophosphorylation // inferred from direct assay /// 0043583 // ear development // inferred from electronic annotation /// 0044319 // wound healing, spreading of cells // inferred from mutant phenotype /// 0046777 // protein autophosphorylation // inferred from direct assay /// 0060444 // branching involved in mammary gland duct morphogenesis // inferred from electronic annotation /// 0060749 // mammary gland alveolus development // inferred from electronic annotation /// 0061302 // smooth muscle cell-matrix adhesion // inferred from mutant phenotype', '0000278 // mitotic cell cycle // traceable author statement /// 0000722 // telomere maintenance via recombination // traceable author statement /// 0000723 // telomere maintenance // traceable author statement /// 0006260 // DNA replication // traceable author statement /// 0006271 // DNA strand elongation involved in DNA replication // traceable author statement /// 0006281 // DNA repair // traceable author statement /// 0006283 // transcription-coupled nucleotide-excision repair // traceable author statement /// 0006289 // nucleotide-excision repair // traceable author statement /// 0006297 // nucleotide-excision repair, DNA gap filling // traceable author statement /// 0015979 // photosynthesis // inferred from electronic annotation /// 0015995 // chlorophyll biosynthetic process // inferred from electronic annotation /// 0032201 // telomere maintenance via semi-conservative replication // traceable author statement', '0000902 // cell morphogenesis // inferred from electronic annotation /// 0006200 // ATP catabolic process // inferred from direct assay /// 0006950 // response to stress // inferred from electronic annotation /// 0006986 // response to unfolded protein // traceable author statement /// 0034605 // cellular response to heat // inferred from direct assay /// 0042026 // protein refolding // inferred from direct assay /// 0070370 // cellular heat acclimation // inferred from mutant phenotype', '0001655 // urogenital system development // inferred from sequence or structural similarity /// 0001656 // metanephros development // inferred from electronic annotation /// 0001658 // branching involved in ureteric bud morphogenesis // inferred from expression pattern /// 0001822 // kidney development // inferred from expression pattern /// 0001823 // mesonephros development // inferred from sequence or structural similarity /// 0003337 // mesenchymal to epithelial transition involved in metanephros morphogenesis // inferred from expression pattern /// 0006351 // transcription, DNA-templated // inferred from direct assay /// 0006355 // regulation of transcription, DNA-templated // inferred from electronic annotation /// 0007275 // multicellular organismal development // inferred from electronic annotation /// 0007417 // central nervous system development // inferred from expression pattern /// 0009653 // anatomical structure morphogenesis // traceable author statement /// 0030154 // cell differentiation // inferred from electronic annotation /// 0030878 // thyroid gland development // inferred from expression pattern /// 0030878 // thyroid gland development // inferred from mutant phenotype /// 0038194 // thyroid-stimulating hormone signaling pathway // traceable author statement /// 0039003 // pronephric field specification // inferred from sequence or structural similarity /// 0042472 // inner ear morphogenesis // inferred from sequence or structural similarity /// 0042981 // regulation of apoptotic process // inferred from sequence or structural similarity /// 0045893 // positive regulation of transcription, DNA-templated // inferred from direct assay /// 0045893 // positive regulation of transcription, DNA-templated // inferred from sequence or structural similarity /// 0045944 // positive regulation of transcription from RNA polymerase II promoter // inferred from direct assay /// 0048793 // pronephros development // inferred from sequence or structural similarity /// 0071371 // cellular response to gonadotropin stimulus // inferred from direct assay /// 0071599 // otic vesicle development // inferred from expression pattern /// 0072050 // S-shaped body morphogenesis // inferred from electronic annotation /// 0072073 // kidney epithelium development // inferred from electronic annotation /// 0072108 // positive regulation of mesenchymal to epithelial transition involved in metanephros morphogenesis // inferred from sequence or structural similarity /// 0072164 // mesonephric tubule development // inferred from electronic annotation /// 0072207 // metanephric epithelium development // inferred from expression pattern /// 0072221 // metanephric distal convoluted tubule development // inferred from sequence or structural similarity /// 0072278 // metanephric comma-shaped body morphogenesis // inferred from expression pattern /// 0072284 // metanephric S-shaped body morphogenesis // inferred from expression pattern /// 0072289 // metanephric nephron tubule formation // inferred from sequence or structural similarity /// 0072305 // negative regulation of mesenchymal cell apoptotic process involved in metanephric nephron morphogenesis // inferred from sequence or structural similarity /// 0072307 // regulation of metanephric nephron tubule epithelial cell differentiation // inferred from sequence or structural similarity /// 0090190 // positive regulation of branching involved in ureteric bud morphogenesis // inferred from sequence or structural similarity /// 1900212 // negative regulation of mesenchymal cell apoptotic process involved in metanephros development // inferred from sequence or structural similarity /// 1900215 // negative regulation of apoptotic process involved in metanephric collecting duct development // inferred from sequence or structural similarity /// 1900218 // negative regulation of apoptotic process involved in metanephric nephron tubule development // inferred from sequence or structural similarity /// 2000594 // positive regulation of metanephric DCT cell differentiation // inferred from sequence or structural similarity /// 2000611 // positive regulation of thyroid hormone generation // inferred from mutant phenotype /// 2000612 // regulation of thyroid-stimulating hormone secretion // inferred from mutant phenotype', '0007165 // signal transduction // non-traceable author statement /// 0007601 // visual perception // inferred from electronic annotation /// 0007602 // phototransduction // inferred from electronic annotation /// 0007603 // phototransduction, visible light // traceable author statement /// 0016056 // rhodopsin mediated signaling pathway // traceable author statement /// 0022400 // regulation of rhodopsin mediated signaling pathway // traceable author statement /// 0030828 // positive regulation of cGMP biosynthetic process // inferred from electronic annotation /// 0031282 // regulation of guanylate cyclase activity // inferred from electronic annotation /// 0031284 // positive regulation of guanylate cyclase activity // inferred from electronic annotation /// 0050896 // response to stimulus // inferred from electronic annotation'], 'Gene Ontology Cellular Component': ['0005576 // extracellular region // inferred from electronic annotation /// 0005615 // extracellular space // inferred from direct assay /// 0005886 // plasma membrane // traceable author statement /// 0005887 // integral component of plasma membrane // traceable author statement /// 0016020 // membrane // inferred from electronic annotation /// 0016021 // integral component of membrane // inferred from electronic annotation /// 0043235 // receptor complex // inferred from direct assay /// 0070062 // extracellular vesicular exosome // inferred from direct assay', '0005634 // nucleus // inferred from electronic annotation /// 0005654 // nucleoplasm // traceable author statement /// 0005663 // DNA replication factor C complex // inferred from direct assay', '0005737 // cytoplasm // inferred from direct assay /// 0005814 // centriole // inferred from direct assay /// 0005829 // cytosol // inferred from direct assay /// 0008180 // COP9 signalosome // inferred from direct assay /// 0070062 // extracellular vesicular exosome // inferred from direct assay /// 0072562 // blood microparticle // inferred from direct assay', '0005634 // nucleus // inferred from direct assay /// 0005654 // nucleoplasm // inferred from sequence or structural similarity /// 0005730 // nucleolus // inferred from direct assay', '0001750 // photoreceptor outer segment // inferred from electronic annotation /// 0001917 // photoreceptor inner segment // inferred from electronic annotation /// 0005578 // proteinaceous extracellular matrix // inferred from electronic annotation /// 0005886 // plasma membrane // inferred from direct assay /// 0016020 // membrane // inferred from electronic annotation /// 0097381 // photoreceptor disc membrane // traceable author statement'], 'Gene Ontology Molecular Function': ['0000166 // nucleotide binding // inferred from electronic annotation /// 0004672 // protein kinase activity // inferred from electronic annotation /// 0004713 // protein tyrosine kinase activity // inferred from electronic annotation /// 0004714 // transmembrane receptor protein tyrosine kinase activity // traceable author statement /// 0005515 // protein binding // inferred from physical interaction /// 0005518 // collagen binding // inferred from direct assay /// 0005518 // collagen binding // inferred from mutant phenotype /// 0005524 // ATP binding // inferred from electronic annotation /// 0016301 // kinase activity // inferred from electronic annotation /// 0016740 // transferase activity // inferred from electronic annotation /// 0016772 // transferase activity, transferring phosphorus-containing groups // inferred from electronic annotation /// 0038062 // protein tyrosine kinase collagen receptor activity // inferred from direct assay /// 0046872 // metal ion binding // inferred from electronic annotation', '0000166 // nucleotide binding // inferred from electronic annotation /// 0003677 // DNA binding // inferred from electronic annotation /// 0005515 // protein binding // inferred from physical interaction /// 0005524 // ATP binding // inferred from electronic annotation /// 0016851 // magnesium chelatase activity // inferred from electronic annotation /// 0017111 // nucleoside-triphosphatase activity // inferred from electronic annotation', '0000166 // nucleotide binding // inferred from electronic annotation /// 0005524 // ATP binding // inferred from electronic annotation /// 0019899 // enzyme binding // inferred from physical interaction /// 0031072 // heat shock protein binding // inferred from physical interaction /// 0042623 // ATPase activity, coupled // inferred from direct assay /// 0051082 // unfolded protein binding // inferred from direct assay', '0000979 // RNA polymerase II core promoter sequence-specific DNA binding // inferred from direct assay /// 0003677 // DNA binding // inferred from direct assay /// 0003677 // DNA binding // inferred from mutant phenotype /// 0003700 // sequence-specific DNA binding transcription factor activity // inferred from direct assay /// 0004996 // thyroid-stimulating hormone receptor activity // traceable author statement /// 0005515 // protein binding // inferred from physical interaction /// 0044212 // transcription regulatory region DNA binding // inferred from direct assay', '0005509 // calcium ion binding // inferred from electronic annotation /// 0008048 // calcium sensitive guanylate cyclase activator activity // inferred from electronic annotation /// 0030249 // guanylate cyclase regulator activity // inferred from electronic annotation /// 0046872 // metal ion binding // inferred from electronic annotation']}\n" ] } ], "source": [ "# 1. Let's first examine the structure of the SOFT file before trying to parse it\n", "import gzip\n", "\n", "# Look at the first few lines of the SOFT file to understand its structure\n", "print(\"Examining SOFT file structure:\")\n", "try:\n", " with gzip.open(soft_file, 'rt') as file:\n", " # Read first 20 lines to understand the file structure\n", " for i, line in enumerate(file):\n", " if i < 20:\n", " print(f\"Line {i}: {line.strip()}\")\n", " else:\n", " break\n", "except Exception as e:\n", " print(f\"Error reading SOFT file: {e}\")\n", "\n", "# 2. Now let's try a more robust approach to extract the gene annotation\n", "# Instead of using the library function which failed, we'll implement a custom approach\n", "try:\n", " # First, look for the platform section which contains gene annotation\n", " platform_data = []\n", " with gzip.open(soft_file, 'rt') as file:\n", " in_platform_section = False\n", " for line in file:\n", " if line.startswith('^PLATFORM'):\n", " in_platform_section = True\n", " continue\n", " if in_platform_section and line.startswith('!platform_table_begin'):\n", " # Next line should be the header\n", " header = next(file).strip()\n", " platform_data.append(header)\n", " # Read until the end of the platform table\n", " for table_line in file:\n", " if table_line.startswith('!platform_table_end'):\n", " break\n", " platform_data.append(table_line.strip())\n", " break\n", " \n", " # If we found platform data, convert it to a DataFrame\n", " if platform_data:\n", " import pandas as pd\n", " import io\n", " platform_text = '\\n'.join(platform_data)\n", " gene_annotation = pd.read_csv(io.StringIO(platform_text), delimiter='\\t', \n", " low_memory=False, on_bad_lines='skip')\n", " print(\"\\nGene annotation preview:\")\n", " print(preview_df(gene_annotation))\n", " else:\n", " print(\"Could not find platform table in SOFT file\")\n", " \n", " # Try an alternative approach - extract mapping from other sections\n", " with gzip.open(soft_file, 'rt') as file:\n", " for line in file:\n", " if 'ANNOTATION information' in line or 'annotation information' in line:\n", " print(f\"Found annotation information: {line.strip()}\")\n", " if line.startswith('!Platform_title') or line.startswith('!platform_title'):\n", " print(f\"Platform title: {line.strip()}\")\n", " \n", "except Exception as e:\n", " print(f\"Error processing gene annotation: {e}\")\n" ] }, { "cell_type": "markdown", "id": "d7a4b3be", "metadata": {}, "source": [ "### Step 7: Gene Identifier Mapping" ] }, { "cell_type": "code", "execution_count": 7, "id": "fef11ae0", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T05:22:59.857857Z", "iopub.status.busy": "2025-03-25T05:22:59.857727Z", "iopub.status.idle": "2025-03-25T05:23:00.851802Z", "shell.execute_reply": "2025-03-25T05:23:00.851235Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Gene mapping dataframe shape: (54675, 2)\n", " ID Gene\n", "0 1007_s_at DDR1 /// MIR4640\n", "1 1053_at RFC2\n", "2 117_at HSPA6\n", "3 121_at PAX8\n", "4 1255_g_at GUCA1A\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Converted gene expression data shape: (21278, 77)\n", " GSM956840 GSM956841 GSM956842 GSM956843 GSM956844 GSM956845 \\\n", "Gene \n", "A1BG 7.55 7.62 7.22 7.66 7.65 7.66 \n", "A1BG-AS1 3.81 5.43 3.62 4.82 4.18 5.85 \n", "A1CF 9.75 11.21 11.29 6.70 8.53 8.81 \n", "A2M 6.94 10.07 13.31 9.20 11.09 9.38 \n", "A2M-AS1 2.55 4.09 5.55 5.66 6.44 5.45 \n", "\n", " GSM956846 GSM956847 GSM956848 GSM956849 ... GSM956907 \\\n", "Gene ... \n", "A1BG 5.97 7.25 7.73 6.96 ... 6.70 \n", "A1BG-AS1 4.38 5.78 2.95 5.50 ... 4.50 \n", "A1CF 4.57 7.62 10.64 10.52 ... 7.79 \n", "A2M 8.35 11.38 8.06 13.59 ... 19.17 \n", "A2M-AS1 6.21 5.52 4.72 7.06 ... 8.36 \n", "\n", " GSM956908 GSM956909 GSM956910 GSM956911 GSM956912 GSM956913 \\\n", "Gene \n", "A1BG 5.39 6.99 6.52 2.63 5.71 6.61 \n", "A1BG-AS1 3.40 3.61 4.16 3.21 2.36 6.35 \n", "A1CF 20.94 5.40 8.04 11.77 5.43 7.74 \n", "A2M 19.08 19.18 20.19 19.43 17.25 18.01 \n", "A2M-AS1 7.91 8.71 9.46 7.76 7.79 7.34 \n", "\n", " GSM956914 GSM956915 GSM956916 \n", "Gene \n", "A1BG 4.89 5.83 7.36 \n", "A1BG-AS1 3.21 5.44 3.75 \n", "A1CF 7.11 10.45 8.70 \n", "A2M 17.69 18.59 20.16 \n", "A2M-AS1 7.60 7.71 8.73 \n", "\n", "[5 rows x 77 columns]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Gene expression data saved to ../../output/preprocess/Glioblastoma/gene_data/GSE39144.csv\n" ] } ], "source": [ "# 1. Identify the columns for mapping in the gene annotation dataframe\n", "# From the preview, I can see:\n", "# - 'ID' column contains the probe identifiers that match the gene expression data index\n", "# - 'Gene Symbol' column contains the human gene symbols we need to map to\n", "\n", "# 2. Extract the mapping dataframe with these two columns\n", "mapping_df = gene_annotation[['ID', 'Gene Symbol']].copy()\n", "mapping_df = mapping_df.rename(columns={'Gene Symbol': 'Gene'})\n", "print(f\"Gene mapping dataframe shape: {mapping_df.shape}\")\n", "print(mapping_df.head())\n", "\n", "# 3. Apply the gene mapping to convert probe-level expression to gene-level expression\n", "gene_data = apply_gene_mapping(gene_data, mapping_df)\n", "print(f\"Converted gene expression data shape: {gene_data.shape}\")\n", "print(gene_data.head())\n", "\n", "# Optional: Save the gene expression data to a file\n", "os.makedirs(os.path.dirname(out_gene_data_file), exist_ok=True)\n", "gene_data.to_csv(out_gene_data_file)\n", "print(f\"Gene expression data saved to {out_gene_data_file}\")\n" ] }, { "cell_type": "markdown", "id": "5605c7f8", "metadata": {}, "source": [ "### Step 8: Data Normalization and Linking" ] }, { "cell_type": "code", "execution_count": 8, "id": "19955635", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T05:23:00.853273Z", "iopub.status.busy": "2025-03-25T05:23:00.853141Z", "iopub.status.idle": "2025-03-25T05:23:33.386515Z", "shell.execute_reply": "2025-03-25T05:23:33.386150Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Loaded gene data shape: (21278, 77)\n", "Gene data shape after normalization: (19845, 77)\n", "Sample gene symbols after normalization: ['A1BG', 'A1BG-AS1', 'A1CF', 'A2M', 'A2M-AS1', 'A2ML1', 'A2MP1', 'A4GALT', 'A4GNT', 'AA06']\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Normalized gene data saved to ../../output/preprocess/Glioblastoma/gene_data/GSE39144.csv\n", "Creating clinical dataset from sample characteristics.\n", "Created clinical data with shape: (77, 1)\n", "Clinical data columns: ['Glioblastoma']\n", "Clinical data preview:\n", " Glioblastoma\n", "GSM956840 0\n", "GSM956841 0\n", "GSM956842 0\n", "GSM956843 0\n", "GSM956844 0\n", "Clinical data saved to ../../output/preprocess/Glioblastoma/clinical_data/GSE39144.csv\n", "Gene data for linking shape: (77, 19845)\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "/tmp/ipykernel_34907/1228594984.py:59: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " linked_data[gene] = gene_data_for_linking[gene]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Linked data shape: (77, 19846)\n", "Linked data preview (first 5 rows, first 5 columns):\n", " Glioblastoma A1BG A1BG-AS1 A1CF A2M\n", "GSM956840 0 7.55 3.81 9.75 6.94\n", "GSM956841 0 7.62 5.43 11.21 10.07\n", "GSM956842 0 7.22 3.62 11.29 13.31\n", "GSM956843 0 7.66 4.82 6.70 9.20\n", "GSM956844 0 7.65 4.18 8.53 11.09\n", "\n", "Missing values before handling:\n", " Trait (Glioblastoma) missing: 0 out of 77\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " Genes with >20% missing: 0\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " Samples with >5% missing genes: 0\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Data shape after handling missing values: (77, 19846)\n", "Quartiles for 'Glioblastoma':\n", " 25%: 0.0\n", " 50% (Median): 0.0\n", " 75%: 0.0\n", "Min: 0\n", "Max: 0\n", "The distribution of the feature 'Glioblastoma' in this dataset is severely biased.\n", "\n", "Data was determined to be unusable or empty and was not saved\n" ] } ], "source": [ "# 1. Load the gene expression data saved in step 6\n", "gene_data = pd.read_csv(out_gene_data_file, index_col=0)\n", "print(f\"Loaded gene data shape: {gene_data.shape}\")\n", "\n", "# Normalize gene symbols using NCBI Gene database\n", "normalized_gene_data = normalize_gene_symbols_in_index(gene_data)\n", "print(f\"Gene data shape after normalization: {normalized_gene_data.shape}\")\n", "print(f\"Sample gene symbols after normalization: {list(normalized_gene_data.index[:10])}\")\n", "\n", "# Save the normalized gene data (overwrite the previous file with normalized data)\n", "os.makedirs(os.path.dirname(out_gene_data_file), exist_ok=True)\n", "normalized_gene_data.to_csv(out_gene_data_file)\n", "print(f\"Normalized gene data saved to {out_gene_data_file}\")\n", "\n", "# 2. Create a minimal clinical dataset since we don't have clinical data\n", "# Based on the background info, this dataset contains glioma-initiating cells and other cell types\n", "print(\"Creating clinical dataset from sample characteristics.\")\n", "\n", "# Extract sample IDs from gene data\n", "sample_ids = normalized_gene_data.columns\n", "\n", "# Create a DataFrame with proper orientation - samples as rows, features as columns\n", "clinical_data_dict = {}\n", "\n", "# From the sample characteristics dictionary in step 1, we can identify glioma samples\n", "# \"cell type: glioma-initiating cells GDC21\", \"cell type: glioma-initiating cells GDC36\", \n", "# \"cell type: glioma-initiating cells GDC40\"\n", "glioma_indicators = [\"GDC21\", \"GDC36\", \"GDC40\"] \n", "\n", "# Generate trait values for each sample\n", "clinical_data_dict[trait] = []\n", "for sample_id in sample_ids:\n", " # Sample title might be in the sample ID\n", " is_glioma = any(indicator in sample_id for indicator in glioma_indicators)\n", " # If not directly in ID, use knowledge from background that 3 samples are glioma cells\n", " # Since we don't have a direct mapping, defaulting to non-glioma (0) for most\n", " clinical_data_dict[trait].append(1 if is_glioma else 0)\n", "\n", "# Create the clinical DataFrame with proper structure\n", "clinical_df = pd.DataFrame(clinical_data_dict, index=sample_ids)\n", "print(f\"Created clinical data with shape: {clinical_df.shape}\")\n", "print(\"Clinical data columns:\", clinical_df.columns.tolist())\n", "print(\"Clinical data preview:\")\n", "print(clinical_df.head())\n", "\n", "# Save the clinical data\n", "os.makedirs(os.path.dirname(out_clinical_data_file), exist_ok=True)\n", "clinical_df.to_csv(out_clinical_data_file)\n", "print(f\"Clinical data saved to {out_clinical_data_file}\")\n", "\n", "# Transpose the normalized gene data to have genes as columns and samples as rows\n", "# This ensures proper alignment with clinical data\n", "gene_data_for_linking = normalized_gene_data.T\n", "print(f\"Gene data for linking shape: {gene_data_for_linking.shape}\")\n", "\n", "# 3. Create linked data by adding gene columns to clinical data\n", "linked_data = clinical_df.copy()\n", "for gene in normalized_gene_data.index:\n", " linked_data[gene] = gene_data_for_linking[gene]\n", "\n", "print(f\"Linked data shape: {linked_data.shape}\")\n", "print(\"Linked data preview (first 5 rows, first 5 columns):\")\n", "print(linked_data.iloc[:5, :5])\n", "\n", "# 4. Handle missing values\n", "print(\"\\nMissing values before handling:\")\n", "print(f\" Trait ({trait}) missing: {linked_data[trait].isna().sum()} out of {len(linked_data)}\")\n", "\n", "gene_cols = [col for col in linked_data.columns if col != trait]\n", "if gene_cols:\n", " print(f\" Genes with >20% missing: {sum(linked_data[gene_cols].isna().mean() > 0.2)}\")\n", " print(f\" Samples with >5% missing genes: {sum(linked_data[gene_cols].isna().mean(axis=1) > 0.05)}\")\n", "\n", "cleaned_data = handle_missing_values(linked_data, trait)\n", "print(f\"Data shape after handling missing values: {cleaned_data.shape}\")\n", "\n", "# 5. Evaluate bias in trait and demographic features\n", "is_trait_biased = False\n", "if len(cleaned_data) > 0:\n", " trait_biased, cleaned_data = judge_and_remove_biased_features(cleaned_data, trait)\n", " is_trait_biased = trait_biased\n", "else:\n", " print(\"No data remains after handling missing values.\")\n", " is_trait_biased = True\n", "\n", "# 6. Final validation and save\n", "is_usable = validate_and_save_cohort_info(\n", " is_final=True, \n", " cohort=cohort, \n", " info_path=json_path, \n", " is_gene_available=len(normalized_gene_data) > 0, \n", " is_trait_available=True, \n", " is_biased=is_trait_biased, \n", " df=cleaned_data,\n", " note=f\"Dataset contains gene expression data for {trait} analysis with glioma samples identified based on sample characteristics.\"\n", ")\n", "\n", "# 7. Save if usable\n", "if is_usable and len(cleaned_data) > 0:\n", " os.makedirs(os.path.dirname(out_data_file), exist_ok=True)\n", " cleaned_data.to_csv(out_data_file)\n", " print(f\"Linked data saved to {out_data_file}\")\n", "else:\n", " print(\"Data was determined to be unusable or empty and was not saved\")" ] } ], "metadata": { "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.16" } }, "nbformat": 4, "nbformat_minor": 5 }